Psi4NumPy demonstrates the use of efficient computational kernels from the open- source Psi4 program through the popular NumPy library for linear algebra in Python to facilitate the rapid development of clear, understandable Python computer code for new quantum chemical methods, while maintaining a relatively low execution time. Using these tools, reference implementations have been created for a number of methods, including self-consistent field (SCF), SCF response, many-body perturbation theory, coupled-cluster theory, configuration interaction, and symmetry-adapted perturbation theory. Further, several reference codes have been integrated into Jupyter notebooks, allowing background and explanatory information to be associated with the imple- mentation. Psi4NumPy tools and associated reference implementations can lower the barrier for future development of quantum chemistry methods. These implementa- tions also demonstrate the power of the hybrid C++/Python programming approach employed by the Psi4 program.

Scientific modeling and simulation software is ubiquitous at Sandia National Laboratories and is integral to providing empirical justification to critical mission decisions. Models are increasingly being expressed as workflows to simplify the many steps needed in scientific analyses but keeping these models and workflows alive for the decades-long timescales needed by Sandia remains a struggle. Additionally, the manual use and (lack of) maintenance of these models creates significant risks for duplicated work and model capability loss over time from changing personnel and computing environments. To address these issues, we are building the Engineering Common Modeling Framework (ECMF), a platform for scientific model sustainment at Sandia. ECMF enables the automatic evaluation of models over time and will ensure that models created at Sandia are discoverable and ready to be revisited, extended, and reused. In this paper, we report our current and planned capabilities as well as lessons learned from our framework development process.

Time-dependent density functional theory (TD-DFT) within a restricted excitation space is an efficient means to compute core-level excitation energies, using only a small subset of the occupied orbitals. However, core-to-valence excitation energies are significantly underestimated when standard exchange-correlation functionals are used, which is partly traceable to systemic issues with TD-DFT's description of Rydberg and charge-transfer excited states. To mitigate this, we have implemented an empirically modified combination of configuration interaction with single substitutions (CIS) based on Kohn-Sham orbitals, which is known as "DFT/CIS". This semi-empirical approach is well-suited for simulating x-ray near-edge spectra, as it contains sufficient exact exchange to model charge-transfer excitations yet retains DFT's low-cost description of dynamical electron correlation. Empirical corrections to the matrix elements enable semi-quantitative simulation of near-edge x-ray spectra without the need for significant a posteriori shifts; this should be useful in complex molecules and materials with multiple overlapping x-ray edges. Parameter optimization for use with a specific range-separated hybrid functional makes this a black-box method intended for both core and valence spectroscopy. Results herein demonstrate that realistic K-edge absorption and emission spectra can be obtained for second- and third-row elements and 3d transition metals, with promising results for L-edge spectra as well. DFT/CIS calculations require absolute shifts that are considerably smaller than what is typical in TD-DFT.

Interoperability in computational chemistry is elusive, impeded by the independent development of software packages and idiosyncratic nature of their output files. The cclib library was introduced in 2006 as an attempt to improve this situation by providing a consistent interface to the results of various quantum chemistry programs. The shared API across programs enabled by cclib has allowed users to focus on results as opposed to output and to combine data from multiple programs or develop generic downstream tools. Initial development, however, did not anticipate the rapid progress of computational capabilities, novel methods, and new programs; nor did it foresee the growing need for customizability. Here, we recount this history and present cclib 2, focused on extensibility and modularity. We also introduce recent design pivots—the formalization of cclib’s intermediate data representation as a tree-based structure, a new combinator-based parser organization, and parsed chemical properties as extensible objects.

We implemented a screening algorithm for one-electron-three-center overlap integrals over contracted Gaussian-type orbitals into the Q-Chem program package. The respective bounds were derived using shell-bounding Gaussians and the Obara-Saika recurrence relations. Using integral screening, we reduced the computational scaling of the Gaussians On Surface Tesserae Simulate HYdrostatic Pressure (GOSTSHYP) model in terms of calculation time and memory usage to a linear relationship with the tesserae used to discretize the surface area. Further code improvements allowed for additional performance boosts. To demonstrate the algorithm's better performance, we calculated the compressibility of fullerenes up to C180, where we were originally limited to C40 due to the high RAM usage of GOSTSHYP.

We present a new software package called M-Chem that is designed from scratch in C++ and parallelized on shared-memory multi-core architectures to facilitate efficient molecular simulations. Currently, M-Chem is a fast molecular dynamics (MD) engine that supports the evaluation of energies and forces from two-body to many-body all-atom potentials, reactive force fields, coarse-grained models, combined quantum mechanics molecular mechanics (QM/MM) models, and external force drivers from machine learning, augmented by algorithms that are focused on gains in computational simulation times. M-Chem also includes a range of standard simulation capabilities including thermostats, barostats, multi-timestepping, and periodic cells, as well as newer methods such as fast extended Lagrangians and high quality electrostatic potential generation. At present M-Chem is a developer friendly environment in which we encourage new software contributors from diverse fields to build their algorithms, models, and methods in our modular framework. The long-term objective of M-Chem is to create an interdisciplinary platform for computational methods with applications ranging from biomolecular simulations, reactive chemistry, to materials research.

The infrared spectra of EDTA complexed with Ca2+ and Mg2+ contain, to date, unidentified vibrational bands. This study assigns the peaks in the linear and two-dimensional infrared spectra of EDTA, with and without either Ca2+ or Mg2+ ions. Two-dimensional infrared spectroscopy and DFT calculations reveal that, in both the presence and absence of ions, the carboxylate symmetric stretch and the terminal CH bending vibrations mix. We introduce a method to calculate participation coefficients that quantify the contribution of the carboxylate symmetric stretch, CH wag, CH twist, and CH scissor in the 1400-1550 cm-1 region. With the help of participation coefficients, we assign the 1400-1430 cm-1 region to the carboxylate symmetric stretch, which can mix with CH modes. We assign the 1000-1380 cm-1 region to CH twist modes, the 1380-1430 cm-1 region to wag modes, and the 1420-1650 cm-1 region to scissor modes. The difference in binding geometry between the carboxylate-Ca2+ and carboxylate-Mg2+ complex manifests as new diagonal and cross-peaks between the mixed modes in the two complexes. The small Mg2+ ion binds EDTA tighter than the Ca2+ ion, which causes a redshift of the COO symmetric stretches of the sagittal carboxylates. Energy decomposition analysis further characterizes the importance of electrostatics and deformation energy in the bound complexes.

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

Extraction and Hypothesis Generation System Manling Li, Ying Lin, Ananya Subburathinam, Spencer Whitehead, Xiaoman Pan, Di Lu, Qingyun Wang, Tongtao Zhang, Lifu Huang, Heng Ji 1 University of Illinois at Urbana-Champaign hengji@illinois.edu Alireza Zareian, Hassan Akbari, Brian Chen, Bo Wu, Emily Allaway, Shih-Fu Chang, Kathleen McKeown 2 Columbia University sc250@columbia.edu, kathy@cs.columbia.edu Yixiang Yao, Jennifer Chen, Eric Berquist, Kexuan Sun, Xujun Peng, Ryan Gabbard Marjorie Freedman, Pedro Szekely, T.K. Satish Kumar 3 Information Sciences Institute, University of Southern California mrf@isi.edu Arka Sadhu, Ram Nevatia University of Southern California nevatia@usc.edu Miguel Rodriguez5, Yifan Wang5, Yang Bai5, Ali Sadeghian4, Daisy Zhe Wang5 5 University of Florida daisyw@ufl.edu

Psi4NumPy demonstrates the use of efficient computational kernels from the open-source Psi4 program through the popular NumPy library for linear algebra in Python to facilitate the rapid development of clear, understandable Python computer code for new quantum chemical methods, while maintaining a relatively low execution time. Using these tools, reference implementations have been created for a number of methods, including self-consistent field (SCF), SCF response, many-body perturbation theory, coupled-cluster theory, configuration interaction, and symmetry-adapted perturbation theory. Furthermore, several reference codes have been integrated into Jupyter notebooks, allowing background, underlying theory, and formula information to be associated with the implementation. Psi4NumPy tools and associated reference implementations can lower the barrier for future development of quantum chemistry methods. These implementations also demonstrate the power of the hybrid C++/Python programming approach employed by the Psi4 program.

We present a first principles approach for decomposing molecular linear response properties into orthogonal (additive) plus non-orthogonal/cooperative contributions. This approach enables one to 1) identify the contributions of molecular building blocks like functional groups or monomer units to a given response property and 2) quantify cooperativity between these contributions. In analogy to the self consistent field method for molecular interactions, SCF(MI), we term our approach LR(MI). The theory, implementation and pilot data are described in detail in the manuscript and supporting information.

Spectroscopy, the molecular response to electromagnetic radiation of different wavelengths, is one of the most powerful experimental tools for interrogating a molecule's structure and dynamics as it interacts with its environment. However, relating a spectroscopic signature to a molecular picture relies on sophisticated computational approaches, which offer a wealth of methods for identifying structures, intermolecular interactions, and their correlation with spectroscopic response. This thesis focuses on the how to correlate a molecule's structure and interactions with its environment via ab initio calculation of spectroscopic parameters. To build a molecular picture of carbon dioxide dynamics in ionic liquids (ILs), quantum chemical calculations on small clusters qualitatively reproduced the experimental ordering for carbon dioxide's asymmetric vibrational stretch peak position which shifts when dissolved in a series of ILs with varying anions. To uncover the physical origin of the shift, the language of decomposition analysis based on absolutely localized molecular orbitals (ALMO-EDA) was translated from energies to vibrational frequencies. Geometric distortion of carbon dioxide, as a result of charge transfer (CT) from the anion into the carbon dioxide, is the driving force for differentiating the carbon dioxide asymmetric stretch shift in different IL anions. After validating these simple models, we further decomposed the CT contribution into geometry and curvature mechanisms, finding that CT is a significant contributor in both the geometry optimization and frequency calculation steps. A comparison between ALMO-EDA and symmetry-adapted perturbation theory (SAPT) showed that while dispersion dominates the binding energy, excellent correlation between both total interaction energies and individual components for ALMO-EDA and SAPT validates the use of DFT, enabling the construction of a semiempirical spectroscopic map. This decomposition presented the first application of an EDA outside the energy realm into molecular properties; however, it is not generally applicable to arbitrary perturbations. A reformulation of the canonical linear response equations for use with ALMOs provides a direct connection between EDA terms and their corresponding contribution to spectra. Results for argon-lithium cation dimer polarizabilities show that allowing CT is equally important in both the underlying ground-state wavefunction and the response calculation, and should not be confused with basis set superposition error.